The present invention generally relates to tools for assisting incontinent subjects, and more specifically, to cognitive-based tools and methods for care and charge of incontinent individuals or animals.
Young children, animals, and adults with disabilities may have trouble communicating biological needs to those around them. For example, an adult suffering from the late stages of Amyotrophic Lateral Sclerosis (ALS) may not have the ability and/or strength to communicate, verbally or otherwise, the need to relieve themselves. Often times such individuals require assistance with that task. Young children and animals may also be unable to communicate, or be incognizant of their own need to relieve themselves, which may lead to unsanitary conditions if a caretaker is not aware of the problem until after the child or animal has defecated or urinated.
The phrase “machine learning” broadly describes a function of an electronic system that learns from data. A machine learning system, engine, or module can include a trainable machine learning algorithm that can be trained, such as in an external cloud environment, to learn functional relationships between inputs and outputs that are currently unknown.